Hostname: page-component-78c5997874-8bhkd Total loading time: 0 Render date: 2024-11-05T10:48:37.340Z Has data issue: false hasContentIssue false

Trends in temporal representation and reasoning

Published online by Cambridge University Press:  07 July 2009

Luca Chittaro
Affiliation:
Dipartimento di Matematica e Informatica Università di Udine Via delle Scienze, 206-33100 Udine, Italy (email: {chittaro/ montana} @dimi.uniud.it)
Angelo Montanari
Affiliation:
Dipartimento di Matematica e Informatica Università di Udine Via delle Scienze, 206-33100 Udine, Italy (email: {chittaro/ montana} @dimi.uniud.it)

Extract

Time is one of the most relevant topics in AI. It plays a major role in several of AI research areas, ranging from logical foundations to applications of knowledge-based systems. Despite the ubiquity of time in AI, researchers tend to specialise and focus on time in particular contexts or applications, overlooking meaningful connections between different areas. In an attempt to promote crossfertilisation and reduce isolation, the Temporal Representation and Reasoning (TIME) workshop series was started in 1994. The third edition of the workshop was held on May 19–20 1996 in Key West, FL, with S. D. Goodwin and H. J. Hamilton as General Chairs, and L. Chittaro and A. Montanari as Program Chairs. A particular emphasis was given to the foundational aspects of temporal representation and reasoning through an investigation of the relationships between different approaches to temporal issues in AI, computer science and logic.

Type
Research Article
Copyright
Copyright © Cambridge University Press 1996

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

All the 1996 references appear in: Chittaro, L, Hamilton, H, Goodwin, S, Montanan, A. (eds.), TIME-96: Proceedings of the Third International Workshop on Temporal Representation and Reasoning, IEEE Press, 1996.Google Scholar
Allen, JF, 1983. “Maintaining knowledge about temporal intervals”. Comm. ACM 26 (11) 832843.CrossRefGoogle Scholar
Dechter, R, Meiri, I and Pearl, J, 1991. “Temporal constraint networks”. Artificial Intelligence 49 6195.CrossRefGoogle Scholar
Halpern, JY and Shoham, Y, 1991. “A propositional modal logic of time intervals”. J. ACM 38 (4) 935962.CrossRefGoogle Scholar
Kowalski, R and Sergot, M, 1986. “A logic-based calculus of events”. New Generation Computing 4 6795.CrossRefGoogle Scholar
McCarthy, J and Hayes, PJ, 1969. “Some philosophical problems from the standpoint of artificial intelligence”. In: Meltzer, B and Michie, D. (eds.), Machine Intelligence 4, Edinburgh University Press.Google Scholar
Meiri, I, 1991. “Combining qualitative and quantitative constraints in temporal reasoning”. Proc. of AAAI-91, Anaheim, CA, 260267.Google Scholar
Montanari, A and Pernici, B, 1993. “Temporal reasoning”. In: Tansel, et al. (eds.), Temporal Databases: Theory, Design and Implementation, Benjamin/Cummings.Google Scholar
Nebel, B and Bürckert, HJ, 1995. “Reasoning about temporal relations: a maximal tractable subclass of Allen's Interval Algebra”. J. ACM 42 (1) 4366.CrossRefGoogle Scholar
Sandewall, E, 1994. Reasoning about Change: Time and causation from the standpoint of Artificial Intelligence, Oxford University Press.Google Scholar
Vilain, MB and Kautz, H, 1986. “Constraint propagation algorithms for temporal reasoning”. Proc. of AAAI-86, Philadelphia, PA, 377382.Google Scholar